Joshua Suetterlein

According to our database, Joshua Suetterlein authored at least 18 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance.

Ted Fujimoto, Joshua Suetterlein, Samrat Chatterjee, Auroop R. Ganguly

CoRR, 2024

2023

Finding Your Niche: An Evolutionary Approach to HPC Topologies.

Stephen J. Young, Joshua Suetterlein, Jesun Firoz, Joseph B. Manzano, Kevin J. Barker

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems.

Himanshu Sharma, Joshua D. Suetterlein, Sumathi Lakshmiranganatha, Thomas Flynn, Draguna L. Vrabie, Christine Sweeney, Vinay Ramakrishniah

Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

2022

Extending an asynchronous runtime system for high throughput applications: A case study.

Joshua Suetterlein, Joseph B. Manzano, Andres Marquez, Guang R. Gao

J. Parallel Distributed Comput., 2022

2021

MAPA: multi-accelerator pattern allocation policy for multi-tenant GPU servers.

Kiran Ranganath, Joshua D. Suetterlein, Joseph B. Manzano, Shuaiwen Leon Song, Daniel Wong

Proceedings of the International Conference for High Performance Computing, 2021

LC-MEMENTO: A Memory Model for Accelerated Architectures.

Kiran Ranganath, Jesun Firoz, Joshua Suetterlein, Joseph B. Manzano, Andres Marquez, Mark Raugas, Daniel Wong

Proceedings of the Languages and Compilers for Parallel Computing, 2021

2020

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance.

Joshua Suetterlein, Joseph B. Manzano, Andres Marquez, Guang R. Gao

Proceedings of the 27th IEEE International Conference on High Performance Computing, 2020

Effectively Using Remote I/O For Work Composition in Distributed Workflows.

Ryan D. Friese, Burcu Ozcelik Mutlu, Nathan R. Tallent, Joshua Suetterlein, Jan Strube

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

A Parallel Graph Environment for Real-World Data Analytics Workflows.

Vito Giovanni Castellana, Maurizio Drocco, John Feo, Jesun Sahariar Firoz, Thejaka Amila Kanewala, Andrew Lumsdaine, Joseph B. Manzano, Andres Marquez, Marco Minutoli, Joshua Suetterlein, Antonino Tumeo, Marcin Zalewski

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2019

TAZeR: Hiding the Cost of Remote I/O in Distributed Scientific Workflows.

Joshua Suetterlein, Ryan D. Friese, Nathan R. Tallent, Malachi Schram

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Adaptive Runtime Features for Distributed Graph Algorithms.

Jesun Sahariar Firoz, Marcin Zalewski, Joshua Suetterlein, Andrew Lumsdaine

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

2017

Verification of the Extended Roofline Model for Asynchronous Many Task Runtimes.

Joshua Suetterlein, Joshua Landwehr, Andres Marquez, Joseph B. Manzano, Kevin J. Barker, Guang R. Gao

Proceedings of the Third International Workshop on Extreme Scale Programming Models and Middleware, 2017

Designing Scalable Distributed Memory Models: A Case Study.

Joshua Landwehr, Joshua Suetterlein, Joseph B. Manzano, Andrès Márquez, Kevin J. Barker, Guang R. Gao

Proceedings of the Computing Frontiers Conference, 2017

2016

Asynchronous Runtimes in Action: An Introspective Framework for a Next Gen Runtime.

Joshua Suetterlein, Joshua Landwehr, Andrès Márquez, Joseph B. Manzano, Guang R. Gao

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Extending the Roofline Model for Asynchronous Many-Task Runtimes.

Joshua D. Suetterlein, Joshua Landwehr, Andrès Márquez, Joseph B. Manzano, Guang R. Gao

Proceedings of the 2016 IEEE International Conference on Cluster Computing, 2016

Application characterization at scale: lessons learned from developing a distributed open community runtime system for high performance computing.

Joshua Landwehr, Joshua Suetterlein, Andres Marquez, Joseph B. Manzano, Guang R. Gao

Proceedings of the ACM International Conference on Computing Frontiers, CF'16, 2016

2013

Automatic Locality Exploitation in the Codelet Model.

Chen Chen, Yao Wu, Joshua Suetterlein, Long Zheng, Minyi Guo, Guang R. Gao

Proceedings of the 12th IEEE International Conference on Trust, 2013

An Implementation of the Codelet Model.

Joshua Suetterlein, Stéphane Zuckerman, Guang R. Gao

Proceedings of the Euro-Par 2013 Parallel Processing, 2013